The RealReal is leading the way in authenticated luxury consignment, online and in real life at our brick and mortar locations. Founded in 2011, we’re growing fast and fundamentally changing the way people buy and sell luxury — a multi-billion dollar industry. With a team of in-house experts who inspect every item we sell, our commitment to authenticity sets us apart and creates a foundation of trust with shoppers and consignors. Our mission to extend the life cycle of luxury items is leading innovation in sustainable fashion. We’re proud to promote the circular economy and to be the first luxury member of the Ellen MacArthur Foundation’s prestigious CE100 USA.

Employees at The RealReal are dedicated, collaborative and innovative, and we’re looking for exceptional talent to join our team. Build your career with us and enjoy 401K matching, health, dental and vision insurance, commuter flex spending, healthcare flex spending, generous PTO, a mother’s room, and flexible work hours!

As a Data Scientist at The RealReal you'll drive our automation, personalization and data pipeline initiatives. You will own critical systems throughout the platform and be responsible for their adding new, valuable features, and ensuring that these systems perform correctly.

This position is based in San Francisco, CA and will report to the Director of Data Engineering.

DUTIES & RESPONSIBILITIES

  • Design and test machine learning models to create highly accurate systems used in operations
  • Write production quality code
  • Take ownership of key components, ensuring that they meet the needs of the business.
  • Collaborate with senior management, product management, and other engineers in the development of product
  • Mentor team members to build the company's overall expertise
  • Work to make The RealReal an innovator in the space by bringing passion and new ideas to work every day

REQUIREMENTS

  • A quantitative degree
  • 2-4+ years experience in a similar role
  • 2-4+ years experience in building and evaluating machine learning & deep learning models
  • 2-4+ years experience putting machine learning models into production
  • Fluency in Python & SQL
  • High degree of familiarity with: Sklearn, TensorFlow/Keras, Pytorch
  • An in depth knowledge or project you can showcase your skills
  • Comfortable working in an environment where innovation and change are the norm
  • A passion for building great products

ADDITIONAL REQUIREMENTS

If computer vision:

  • Experience with classical computer vision techniques (image registration, thresholding, camera calibration, keypoint detection, etc)
  • Experience with deep learning applied to computer vision (image classification, object detection, semantic segmentation, GANs, etc)

If data engineering:

  • Experience building sustainable and scalable ETL pipelines
  • Experience with different types of databases (Key-Value, Document, Relational, MPP, etc)
  • Deep experience with cloud architectures (AWS/GCP) using serverless designs and event driven architectures
  • Experience with Kafka/Kinesis/PubSub event-based designs
  • Experience writing and reading from APIs

 

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this Job, the employee is regularly required to sit; use hands to finger, handle, or feel and talk or hear. The employee is occasionally required to stand; walk; reach with hands and arms; climb or balance; stoop, kneel, crouch, or crawl and taste or smell. The employee must occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision.

The RealReal is committed to providing an equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or Veteran status. We will consider qualified applicants for a position regardless of arrest or conviction records, consistent with legal requirements. 

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